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Joint Routing and Charging Problem of Electric Vehicles with Incentive-Aware Customers Considering Spatio-Temporal Charging Prices

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SSRN

SSRN 2022年

作者： Yao, Canqi Chen, Shibo Salazar, Mauro Yang, Zaiyue School of Mechatronics Engineering Harbin Institute of Technology Harbin150000 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering The Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China Control Systems Technology Group Department of Mechanical Engineering Eindhoven University of Technology EindhovenMB 5600 Netherlands

This paper investigates the scheduling problem of a fleet of electric vehicles, providing mobility as a service to a set of time-specified customers, where the operator needs to solve the routing and charging problem jointly for each EV. Hereby we consider incentive-aware customers and propose that the operator offers monetary incentives to customers in exchange for time flexibility. In this way, the fleet operator can achieve a routing and charging schedule with lower costs, whilst the customers receive monetary compensation for their flexibility. Specifically, we first propose a bi-level optimization model whereby the fleet operator optimizes the routing and charging schedule accounting for the spatio-temporal varying charging price, jointly with a monetary incentive to reimburse the delivery time flexibility experienced by the customers. Concurrently the customers choose their own time flexibility by minimizing their own cost. Second, we cope with the computational burden coming from this nonlinear bi-level optimization model with an accurate reformulation approach consisting of the KKT optimality conditions, a Big-M-based linearization method, and the zero duality gap of convex optimization problems. This way, we convert the proposed problem into a single-level optimization problem, which can be solved by a strengthened generalized Benders decomposition method holding a faster convergence rate than the generalized Benders decomposition method. To evaluate the effectiveness of the proposed mathematical model, we carry out numerous simulation experiments by using the VRP-REP data of Belgium. The numerical results showcase that the proposed mathematical model can reduce the delivery fees for the customers together with the cost of operation incurred by the fleet operator. © 2022, The Authors. All rights reserved.

关键词： Sales

Joint Routing and Charging Problem of Electric Vehicles with Incentive-aware Customers Considering Spatio-temporal Charging Prices

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arXiv 2022年

关键词： Sales

Preventive-Corrective Cyber-Defense: Attack-Induced Region Minimization and Cybersecurity Margin Maximization

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arXiv 2023年

作者： Hou, Jiazuo Teng, Fei Yin, Wenqian Song, Yue Hou, Yunhe The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The University of Hong Kong Shenzhen Institute of Research and Innovation Shenzhen518057 China The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom The Department of Control Science and Engineering Tongji University Shanghai201804 China The National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai201210 China The Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai200120 China

False data injection (FDI) cyber-attacks on power systems can be prevented by strategically selecting and protecting a sufficiently large measurement subset, which, however, requires adequate cyber-defense resources for measurement protection. With any given cyber-defense resource, this paper proposes a preventive-corrective cyber-defense strategy, which minimizes the FDI attack-induced region in a preventive manner, followed by maximizing the cybersecurity margin in a corrective manner. First, this paper proposes a preventive cyber-defense strategy that minimizes the volume of the FDI attack-induced region via preventive allocation of any given measurement protection resource. Particularly, a sufficient condition for constructing the FDI unattackable lines is proposed, indicating that the FDI cyber-attack could be locally rather than globally prevented. Then, given a non-empty FDI attack-induced region, this paper proposes a corrective cyber-defense strategy that maximizes the cybersecurity margin, leading to a trade-off between the safest-but-expensive operation point (i.e., Euclidean Chebyshev center) and the cheapest-but-dangerous operation point. Simulation results on a modified IEEE 14 bus system verify the effectiveness and cost-effectiveness of the proposed preventive-corrective cyber-defense strategy. Copyright © 2023, The Authors. All rights reserved.

关键词： Cost effectiveness

Using artificial intelligence to document the hidden RNA virosphere

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四川生理科学杂志 2024年第10期46卷 2345-2345页

作者： Xin Hou National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases State Key Laboratory for Biocontrol School of Medicine Shenzhen Campus of Sun Yat-sen University Sun Yat-sen University Shenzhen China Apsara Lab Alibaba Cloud Intelligence Alibaba Group Hangzhou China Wuhan Centers for Disease Control and Prevention Wuhan China Polar Research Institute of China Shanghai China Department of Nursing The Fifth Affiliated Hospital Sun Yat-sen University Zhuhai China School of Geospatial Engineering and Science Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Sun Yat-sen University Zhuhai China Key Laboratory of Comprehensive Observation of Polar Environment Ministry of Education Sun Yat-sen University Zhuhai China Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary Institute of Biodiversity Science and Institute of Eco-Chongming School of Life Sciences Fudan University Shanghai Shanghai China Centre for Virus Research Westmead Institute for Medical Research Westmead NSW Australia School of Medical Sciences The University of Sydney Sydney NSW 2006 Australia College of Life Sciences Zhejiang University Hangzhou China School of Life Science Guangzhou University Guangzhou China Key Laboratory of Pathogen Infection Prevention and Control (MOE) State Key Laboratory of Respiratory Health and Multimorbidity National Institute of Pathogen Biology Chinese Academy of Medical Sciences & Peking Union Medical College Beijing China School of Public Health (Shenzhen) Shenzhen Campus of Sun Yat-sen University Sun Yat-sen University Shenzhen China Guangzhou National Laboratory Guangzhou International Bio-Island Guangzhou China Department of Infectious Diseases and Public Health Jockey Club College of Veterinary Medicine and Life Sciences City University of Hong Kong Hong Kong SAR China Laboratory of Data Disco

Current metagenomic tools can fail to identify highly divergent RNA *** developed a deep learning algorithm,termed LucaProt,to discover highly divergent RNA-dependent RNA polymerase(RdRP)sequences in 10,487 metatranscriptomes generated from diverse global *** integrates both sequence and predicted structural information,enabling the accurate detection of RdRP *** this approach,we identified 161,979 potential RNA virus species and 180 RNA virus supergroups,including many previously poorly studied groups,as well as RNA virus genomes of exceptional length(up to 47,250 nucleotides)and genomic complexity.

关键词： artificial exceptional integrate

Identifiability Analysis of Noise Covariances for LTI Stochastic systems with Unknown Inputs

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arXiv 2022年

作者： Kong, He Sukkarieh, Salah Arnold, Travis J. Chen, Tianshi Mu, Biqiang Zheng, Wei Xing Shenzhen518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities SUSTech Shenzhen518055 China Sydney Institute for Robotics and Intelligent Systems The University of Sydney NSW2006 Australia Madison WI53704 United States School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Computer Data and Mathematical Sciences Western Sydney University SydneyNSW2751 Australia

Most existing works on optimal filtering of linear time-invariant (LTI) stochastic systems with arbitrary unknown inputs assume perfect knowledge of the covariances of the noises in the filter design. This is impractical and raises the question of whether and under what conditions one can identify the process and measurement noise covariances (denoted as Q and R, respectively) of systems with unknown inputs. This paper considers the identifiability of Q/R using the correlation-based measurement difference approach. More specifically, we establish (i) necessary conditions under which Q and R can be uniquely jointly identified;(ii) necessary and sufficient conditions under which Q can be uniquely identified, when R is known;(iii) necessary conditions under which R can be uniquely identified, when Q is known. It will also be shown that for achieving the results mentioned above, the measurement difference approach requires some decoupling conditions for constructing a stationary time series, which are proved to be sufficient for the well-known strong detectability requirements established by Hautus. © 2022, CC BY.

关键词： Stochastic systems

Two points are enough

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arXiv 2024年

作者： Liu, Hao Zhao, Yanbin Zheng, Huarong Fan, Xiulin Deng, Zhihua Chen, Mengchi Wang, Xingkai Liu, Zhiyang Lu, Jianguo Chen, Jian State Key Laboratory of Fluid Power Components and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Ocean College Zhejiang University Hangzhou China State Key Laboratory of Silicon and Advanced Semiconductor Materials School of Materials Science and Engineering Zhejiang University Hangzhou China Nanyang Technological University Singapore School of Control Science and Engineering Zhejiang University Hangzhou China School of Materials Science and Engineering Tianjin University Tianjin China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

Prognosis and diagnosis play an important role in accelerating the development of lithium-ion batteries, as well as reliable and long-life operation. In this work, we answer an important question: What is the minimum amount of data required to extract features for accurate battery prognosis and diagnosis? Based on the first principle, we successfully extracted the best two-point feature (BTPF) for accurate battery prognosis and diagnosis using the fewest data points (only two) and the simplest feature selection method (Pearson correlation coefficient). The BTPF extraction method is tested on 820 cells from 6 open-source datasets (covering five different chemistry types, seven manufacturers, and three data types). It achieves comparable accuracy to state-of-the-art features in both prognosis and diagnosis tasks. This work challenges the cognition of existing studies on the difficulty of battery prognosis and diagnosis tasks, subverts the fixed pattern of establishing prognosis and diagnosis methods for complex dynamic systems through deliberate feature engineering, highlights the promise of data-driven methods for field battery prognosis and diagnosis applications, and provides a new benchmark for future studies. Copyright © 2024, The Authors. All rights reserved.

关键词： Lithium-ion batteries

Path Planning of the Spherical Robot based on Improved Ant Colony Algorithm 17

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Path Planning of the Spherical Robot based on Improved Ant C...

17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Guo, Jian Huo, Xiaojie Guo, Shuxiang Xu, Jigang Tianjin University of Technology Binshui Xidao Extension 391 Tianjin Key Laboratory for Control Theory Applications In Complicated Systems and Intelligent Robot Laboratory Faculty of Engineering Tianjin300384 China Unit68709 Qinghai Haidong810700 China

ISBN: (纸本)9781728164151

With the development and progress of science and technology, the requirement of intelligent algorithm performance in the field of path planning is constantly improved. It is very important to improve the performance of intelligent algorithm and apply it in the field of path planning. In order to overcome the problem that ant colony algorithm tends to fall into local optimal in the early stage and converge slowly in the late stage. This paper proposed an ant colony algorithm based on adaptive pheromone updating strategy and enhanced negative feedback mechanism. The simulation results show that the improved ant colony algorithm is superior to the traditional ant colony algorithm and solves the problem of insufficient convergence in the early stage and low convergence in the late stage. Finally, the algorithm is tested by spherical robot. The experimental results show that the improved ant colony algorithm overcomes the shortcomings of traditional algorithms and verifies the effectiveness and convergence of the algorithm. © 2020 IEEE.

关键词： Motion planning

A CNN-LSTM Hybrid Model for Ankle Joint Motion Recognition Method Based on sEMG

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A CNN-LSTM Hybrid Model for Ankle Joint Motion Recognition M...

International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Hao-Ran Cheng Guang-Zhong Cao Cai-Hong Li Aibin Zhu Xiaodong Zhang Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots Shenzhen Key Laboratory of Electromagnetic Control College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Institute of Robotics & Intelligent Systems Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots Xi'an China

ISBN: (数字)9781728157153

ISBN: (纸本)9781728157160

A CNN-LSTM hybrid model for ankle joint motion recognition based on surface electromyography (sEMG) signals is proposed in this paper. The traditional recognition method is to manually extract the features from sEMG signals and then use machine learning method to train the model, which relies on prior knowledge and requires a lot of time to test and select good features to obtain high classification accuracy. In this paper, the CNN-LSTM hybrid model is used to identify four ankle joint movements (dorsiflexion, plantar flexion, foot varus and foot eversion). The hybrid model consists of two CNN layers and three LSTM layers. CNN can learn to automatically extract features and LSTM is able to capture long-term correlations of sEMG data. The experiment results show that the proposed model is effective and accurate, thus providing a basis for the subsequent research.

关键词： Feature extraction Convolution Machine learning Logic gates Neurons Kernel Robots

Generation Mechanism and Dual Dynamic Simulations of Surface Patterns in Single-Point Diamond Turning of Single-Crystal Copper

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Research Square

Research Square 2021年

作者： Xiong, Jie Chen, Yanbing Dai, Yuqi Zhang, Guoqing Ran, Jiaqi To, Sandy Shenzhen Key Laboratory of High Performance Nontraditional Manufacturing College of Mechatronics and Control Engineering Shenzhen University Nan-hai Ave 3688 Guangdong Shenzhen518060 China Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots College of Mechatronics and Control Engineering Shenzhen University Nan-hai Ave 3688 Guangdong Shenzhen518060 China State Key Laboratory of Ultra-precision Machining Technology Department of Industrial and Systems Engineering Hong Kong Polytechnic University Kowloon Hong Kong

Single-crystal copper (Cu), whose atom arrangement is in the same direction and has no grain boundary, is widely used in defense technology, civil electronics and network communication. As a diamond turnable material, fan-shaped patterns appear on the machined surface, which affects the machined surface quality and the optical function it carries. Previous studies on the surface generation mechanism in single-point diamond turning (SPDT) of Cu were limited to experimental analysis, while there is a lack of fundamental understanding of the fan-shaped pattern generation mechanism and suppression method. In the present study, the different fan-shaped patterns, surface quality, cutting force and chip morphology of the typical crystal planes (100), (110) and (111) planes of Cu were studied by both theoretical and experimental analyses. A molecular dynamics (MD) simulation was conducted to present the fundamental generation mechanism of the fan-shaped patterns from atom arrangement directions and its angle change with the main cutting direction, while a cutting dynamics model was established to simulate the generation of fan-shaped patterns on the machined surface. Based on theoretical and experimental analysis, it was found that the atom density arrangement directions of Cu and its angle change with © 2021, CC BY.

关键词： Molecular dynamics